Thermodynamics of Sorption Modeling: Advanced Concepts, Databases and Applicability Tests

The lecture summarizes efforts to deliver a chemical base for safety analysis and risk assessment. One major aspect is the substitution of conventional distribution coefficients (Kd values) for the empirical description of sorption processes by surface complexation models (SCM).
The general strategy and examples for current blind predictive capabilities of SCM and the respective database RES³T – the "Rossendorf Expert System for Surface and Sorption Thermodynamics"- are explained.
RES³T is a digitized version of a thermodynamic sorption database as required for the parametrisation of SCM, namely in risk assessment studies.
The approach for the compilation of numerical data includes the collection of the mineral surface characteristics, the selection of reliable data records, the extrapolation to infinite dilution, the normalization to a reference site density and the averaging of selected thermodynamic data records.
The Cu(II) sorption onto goethite and the Np(V) sorption onto hematite were chosen as systems illustrating the blind predictive capabilities. The model predictions represent the experimental values for the adsorbed amount of Cu(II) and Np(V), respectively, expressed as conventional distribution coefficients K_D as required by most performance assessment software, are within one order of magnitude or better.
As an example to illustrate the effect of parameter uncertainty in blind predictions the Np(V) sorption onto haematite was selected. The formally large scatter of pK values as extracted from literature is actually not critical. Even the use of inconsistent values from other electrostatic models will yield similar results.
We can conclude, that for well-defined mineral systems, provided a suitable database is accessible, the SCM approach seems to be promising. More realistic (thermodynamic) approaches can and have to amend the K_D concept.